The bowl phenomenon provides a way of increasing the throughput of som
e production line systems with variable processing times by purposely
unbalancing the line in a certain manner. However, achieving this incr
ease in throughput depends on correctly identifying the values of the
system parameters to estimate the optimal amount of unbalance and then
actually being able to assign work to stations according to the optim
al bowl allocation. In this paper we study the robustness of the bowl
phenomenon by examining the effect of inaccurately estimating the opti
mal amount of unbalance and the effect of deviating from the optimal b
owl allocation. Our results show that the bowl phenomenon is relativel
y robust in the sense that fairly large errors (even 50%) in the amoun
t of unbalance still provide most of the potential improvement in thro
ughput over a perfectly balanced line. Moreover, the throughput still
exceeds that of a perfectly balanced line in most cases even when the
work allocation to each station deviates from the optimal bowl allocat
ion by as much as 10%. We also address the question of whether the opt
imal bowl allocation or the balanced line provides a more robust 'targ
et' when assigning work to stations. When the deviations from these tw
o targets are of the same magnitude, we found that the optimal bowl al
location target yields the larger throughput in most cases, where the
average difference between their throughputs is roughly the same as th
e difference between the optimal throughput and the throughput of a ba
lanced line. Furthermore, for the same magnitude of deviation, the thr
oughput depends more heavily on the direction of the deviation from th
e balanced line than that from the optimal bowl allocation, so that th
e risk of a substantially reduced throughput is much larger when using
the balanced line as the target. Therefore, the optimal bowl allocati
on provides a much more robust target than the balanced line.